Removing parts no longer needed to fix vram

import contextlib

import torch

import gc

from modules import errors

    return cpu

def torch_gc():

    gc.collect()

    if torch.cuda.is_available():

        torch.cuda.empty_cache()

        torch.cuda.ipc_collect()

            state.job_count = p.n_iter

        for n in range(p.n_iter):

        with torch.no_grad(), precision_scope("cuda"), ema_scope():

            if state.interrupted:

                break

                x_samples_ddim = modules.safety.censor_batch(x_samples_ddim)

            for i, x_sample in enumerate(x_samples_ddim):

            with torch.no_grad(), precision_scope("cuda"), ema_scope():

                x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)

                x_sample = x_sample.astype(np.uint8)

                if p.restore_faces:

                with torch.no_grad(), precision_scope("cuda"), ema_scope():

                    if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration:

                        images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration")

                    x_sample = modules.face_restoration.restore_faces(x_sample)

                    devices.torch_gc()

                    x_sample = modules.face_restoration.restore_faces(x_sample)

                    devices.torch_gc()

            with torch.no_grad(), precision_scope("cuda"), ema_scope():

                image = Image.fromarray(x_sample)

                if p.color_corrections is not None and i < len(p.color_corrections):

            state.nextjob()

    with torch.no_grad(), precision_scope("cuda"), ema_scope():

        p.color_corrections = None

        index_of_first_image = 0